von Rosenberg Wilhelm, Chanwimalueang Theerasak, Goverdovsky Valentin, Peters Nicholas S, Papavassiliou Christos, Mandic Danilo P
Department of Electrical and Electronic Engineering, Imperial College London, London, UK.
ElectroCardioMaths Programme, Myocardial Function Section, Imperial College and Imperial NHS Trust, London, UK.
R Soc Open Sci. 2017 Nov 15;4(11):171214. doi: 10.1098/rsos.171214. eCollection 2017 Nov.
Mobile technologies for the recording of vital signs and neural signals are envisaged to underpin the operation of future health services. For practical purposes, unobtrusive devices are favoured, such as those embedded in a helmet or incorporated onto an earplug. However, these locations have so far been underexplored, as the comparably narrow neck impedes the propagation of vital signals from the torso to the head surface. To establish the principles behind electrocardiogram (ECG) recordings from head and ear locations, we first introduce a realistic three-dimensional biophysics model for the propagation of cardiac electric potentials to the head surface, which demonstrates the feasibility of head-ECG recordings. Next, the proposed biophysics propagation model is verified over comprehensive real-world experiments based on head- and in-ear-ECG measurements. It is shown both that the proposed model is an excellent match for the recordings, and that the quality of head- and ear-ECG is sufficient for a reliable identification of the timing and shape of the characteristic P-, Q-, R-, S- and T-waves within the cardiac cycle. This opens up a range of new possibilities in the identification and management of heart conditions, such as myocardial infarction and atrial fibrillation, based on 24/7 continuous in-ear measurements. The study therefore paves the way for the incorporation of the cardiac modality into future 'hearables', unobtrusive devices for health monitoring.
用于记录生命体征和神经信号的移动技术被设想为支撑未来医疗服务运作的基础。出于实际应用的目的,人们更青睐不引人注意的设备,比如嵌入头盔或集成到耳塞中的设备。然而,到目前为止,这些部位尚未得到充分探索,因为相对狭窄的颈部阻碍了生命信号从躯干传播到头部表面。为了确立从头部和耳部位置记录心电图(ECG)背后的原理,我们首先引入一个用于心脏电势向头部表面传播的逼真三维生物物理模型,该模型证明了头部心电图记录的可行性。接下来,基于头部和耳内心电图测量,通过全面的实际实验对所提出的生物物理传播模型进行了验证。结果表明,所提出的模型与记录结果非常匹配,并且头部和耳部心电图的质量足以可靠地识别心动周期内特征性P、Q、R、S和T波的时间和形状。这为基于7×24小时连续耳内测量来识别和管理心脏病(如心肌梗死和心房颤动)开辟了一系列新的可能性。因此,这项研究为将心脏监测模式纳入未来用于健康监测的不引人注意的“可听设备”铺平了道路。